脉象信号的特征提取与识别方法  

Feature extraction and recognition technique for human pulse signals

作　　者：蔡坤宝[1] 曹丁[1] 段云孜 罗德成[3] 刘宗行[1] 

机构地区：[1]重庆大学通信工程学院,重庆400044 [2]重庆市精神病院药物依赖康复中心,重庆400038 [3]第三军医大学高原军事医学系,重庆400038

出　　处：《重庆大学学报（自然科学版）》2011年第10期119-123,共5页Journal of Chongqing University

基　　金：'211工程'三期建设资助项目(S-09102)

摘　　要：中医脉象信号的研究在中医诊断中具有重要的意义。为了探索由中医脉象信号识别海洛因吸毒者的有效方法,研究了中医脉象信号特征提取的倒双谱与三阶倒谱熵算法。在简洁而准确地论述算法的基础上,估计了20例海洛因吸毒者与20例健康正常人脉象信号的倒双谱的对角切片分量。在大量实验结果的基础上,选取对角切片在m=n=1处的抽样幅值、在特定区域内抽样幅值的三阶倒谱熵作为每例脉搏波信号的2个特征参数,并构成特征向量。以平方马氏距离为准则设计了分类器,该分类器对40个特征向量的准确识别率为87.5%。研究结果表明,提出的特征提取与分类器设计方法对海洛因吸毒者脉象信号的识别具有一定的意义。In Chinese traditional medicine,the pulse signal plays an important role for diagnosis.To investigate the effective technique for identifying heroin druggers through the pulse signal,the feature extraction algorithm based on the biocepstrum and the third-order cepstrum entropy of the pulse signal is studied.On the basis of concise and rigorous discussion for the algorithm,the biocepstrum-based diagonal slice components are estimated for human pulse signals of 20 heroin druggers and 20 healthy normal subjects.The magnitude of the sample value of diagonal slice at m=n=1 and the third-order cepstrum entropy of magnitudes of sample values of the diagonal slice within a particular region are used as two feature parameters for every human pulse signal to form a feature vector.A classifier based on the criterion of squared Mahalanobis distance is successfully designed.Applying the designed classifier to 40 feature vectors,the correct identification rate reaches 87.5%.The research result shows that the method of the feature extraction and classifier design presented in is valuable for identifying the human pulse signals of heroin druggers.

关 键 词：脉象信号 倒双谱 模式识别 

分 类 号：R318.04[医药卫生—生物医学工程]